我怎样才能成为一名数据科学家（一）
How can I become a data scientist?
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网友：为了提供更好的服务和增加利润，世界各地公司的传统做法都收集和分析消费者的数据。在今天的数字环境中，我们可能会收集大量的数据，这就需要非传统的数据处理方法和软件。如果你想成为一名数据科学家，那么Learnbay就是你需要的平台。它在线提供灵活的学习的同时在众多领域提供专业化和就业支持......
正文翻译
How can I become a data scientist?
我怎样才能成为一名数据科学家?
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Companies all over the globe have traditionally collected and analyzed data about their consumers in order to provide better service and increase profits. We may collect enormous volumes of data in today's digital environment, which necessitates non-traditional data processing methods and software. If you want to be a Data Scientist, then Learnbay is the platform for you. It offers online flexible learning along with multiple domain specialization and placement support. Read till the end of my answer to get more details.
为了提供更好的服务和增加利润，世界各地公司的传统做法都收集和分析消费者的数据。在今天的数字环境中，我们可能会收集大量的数据，这就需要非传统的数据处理方法和软件。如果你想成为一名数据科学家，那么Learnbay就是你需要的平台。它在线提供灵活的学习的同时在众多领域提供专业化和就业支持。请读完我的答案，了解更多细节。
Data science is a field of study that focuses on extracting knowledge from large amounts of data. Professionals that can transform data analysis into a competitive advantage for their companies are in high demand. A data scientist's job includes developing data-driven business solutions and insights.
Skills To Become A Data Scientist
You'll need to master abilities in the following areas to become a data scientist:
那么什么是数据科学呢？
数据科学是一个专注于从大量数据中提取知识的研究领域。能够通过数据分析让公司更有竞争优势的专业人士需求量很大。数据科学家的工作包括开发数据驱动的业务解决方案和见解。
成为数据科学家的技能
要成为一名数据科学家，你需要掌握以下方面的能力：
#2 Learn how to use statistics, probability, and mathematical analysis to solve problems. Statistics is the branch of science that studies and develops techniques for gathering, analyzing, interpreting, and presenting empirical data. Probability is a metric for determining the possibility of an event occurring. Limits and related notions, such as differentiation, integration, measure, infinite series, and analytic functions, are dealt with in mathematical analysis.
#3 At least one programming language should be mastered. When it comes to data analytics, programming languages like R, Python, and SAS are essential. R is a free statistical computing and graphics environment that supports most Machine Learning methods for Data Analytics, including regression, association, and clustering. Python is a free and open-source programming language. In Data Science, Python libraries such as NumPy and SciPy are employed. SAS can extract, manipulate, organize, and retrieve data from a number of sources, as well as perform statistical analysis on it.
#4 Learn how to clean, manipulate, and organize data using Data Wrangling. R, Python, Flume, and Scoop are all popular data wrangling technologies.
#5 Learn the fundamentals of machine learning. Providing systems with the capacity to learn and improve based on their experiences without having to be expressly programmed to do so. Regressions, Naive Bayes, SVM, K Means Clustering, KNN, and Decision Tree algorithms, to mention a few, are examples of machine learning algorithms.
#6 Having a basic knowledge of Big Data technologies like Apache Spark, Hadoop, Talend, and Tableau, which are used to deal with massive and complicated data that typical data processing applications can't handle.
#7 Improve your capacity to envisage outcomes. Data visualization is the process of combining diverse data sets and visualizing the findings using diagrams, charts, and graphs.
了解如何使用类似甲骨文公司数据库，MySQL公司数据库，微软公司数据库和天睿资讯数据库以在数据库中存储和分析数据。
学习如何使用统计学、概率论和数学分析来解决问题。统计学是研究和开发收集、分析、解释和呈现经验数据的技术的科学分支。概率是确定事件发生可能性的一个指标。数学分析中涉及极限和相关概念，如微分、积分、测度、无穷级数和解析函数。
至少应掌握一种编程语言。在数据分析方面，R、Python和SAS等编程语言至关重要。R是一个免费的统计计算和图形环境，支持大多数用于数据分析的机器学习方法，包括回归、关联和聚类。Python是一种免费的开源编程语言。在数据科学中，使用了诸如NumPy和SciPy之类的Python库。SAS可以从多个源中提取、操作、组织和检索数据，并对其进行统计分析。
学习如何使用数据整理（Data Wrangling）软件清理、操作和组织数据。R、 Python、Flume和Scoop都是流行的数据整理科技。
学习机器学习基础之预测数据分析。提供有能力根据自己的经验（而无需明确编程）学习和改进的系统。且举几种例子：回归、朴素贝叶斯、支持向量机、K均值聚类、KNN和决策树算法等这些都是机器学习算法的例子。
具备Apache Spark、Hadoop、Talend和Tableau等大数据技术的基础知识，这些技术用于处理典型数据处理应用程序无法处理的海量复杂数据。
提高设想结果的能力。数据可视化是将各种数据集结合起来，并使用图表、排行榜和曲线图将结果可视化的过程。
Learnbay’s various courses related to data science prepare you for an exciting career in data science. Some of the key features are as follows.
#1 Domain Specialization
You will find domain-specific courses on Learnbay. Then you may enroll in a domain-specific course on Learnbay in your chosen field. There are a lot of domain-specific courses available on Learnbay such as marketing and Sales Retail, e-commerce, and supply chain, Healthcare pharma & clinical resources, BFSI, Manufacturing mechanical & telecom, Media, Hospitality, and transportation, and Oil, gas, and energy.
#2 Real-time Projects
This course will cover topics in C#, Python, jaxcript, PHP, and other widely-used programming languages. Along with that, you will get the opportunity to work in real-world projects related to fields such as banking, finance, retail, healthcare, telecommunications, and marketing. It will provide you with the information and expertise you need to understand how your preferred programming language is used in that business.
#3 Academic Counselling
Because many schools offer multiple Data Science courses, it might be a little tricky to pick the proper one. Learnbay sets itself apart from the competition by providing students with a career counseling option, in which you may speak with an industry specialist and resolve any of your concerns. Following the session, the counselor will provide you with a personalized learning track that will assist you in completing your learning according to your needs and in the most effective manner possible.
#4 Job Assistance
In most of the data science courses, Learnbay provides you with the opportunity to work under various organizations. After the completion of your course, you get placement support and job assistance. If you don’t get places then you are offered a 100% money-back guarantee.
为数据科学的职业生涯做准备
Learnbay的各种与数据科学相关的课程为你在数据科学领域的激动人心的职业生涯做好准备。以下是一些关键特性。
领域专业化
你可以在Learnbay上找到特定领域的课程。然后，您可以在Learnbay上注册所选领域的特定领域课程。Learnbay上有许多特定领域的课程，如营销和销售零售、电子商务和供应链、医疗保健制药和临床资源、金融服务和保险业、制造机械和电信、媒体、酒店和运输、石油、天然气和能源。
实时项目
本课程将涵盖C#、Python、jaxcript、PHP和其他广泛使用的编程语言的主题。除此之外，你还将有机会从事与银行、金融、零售、医疗保健、电信和营销等领域相关的现实项目。它将为你提供所需的信息和专业知识，以了解你首选的编程语言在该业务中的使用情况。
学术咨询
由于许多学校提供多种数据科学课程，因此选择合适的课程可能有点棘手。Learnbay通过为学生提供职业咨询选项，让自己在竞争中脱颖而出。在这个选项中，你可以与行业专家交谈，并解决你的担忧。课程结束后，辅导员将为您提供个性化的学习途径，帮助您根据需要以最有效的方式完成学习。
就业援助
在大多数数据科学课程中，Learnbay为您提供了在各种组织下工作的机会。完成课程后，你会得到就业支持和工作帮助。如果你找不到地方就业，你会得到100%的退款保证。
Thanks for taking the time to read my answer till the end.
我希望我的回答能帮助你解决问题。Learnbay的数据科学课程提供了行业专家提供的数据科学方面的深入知识，因此获得的证书可以表明你在学习该学科方面取得了重大进展。从事项目和模拟工作，以及回顾案例研究，将为你提供信息和能力，使你在竞争中处于领先地位。
感谢你抽出时间阅读完我的答案。
Abhishek Batchu，数据科学经理(2017-至今)
原创翻译：龙腾网 http://www.ltaaa.cn 转载请注明出处
I will discuss every step that I have taken and also mention the exact Data Science career path for both non-programming /programming backgrounds for all different age groups.
人们对我从一名机械工程学生到数据科学经理的经历感到非常惊讶，这就像坐过山车。
我将讨论我所采取的每一个步骤，同时也会提到对于具有非编程或编程背景的所有不同年龄段的人来说，数据科学的职业道路。
I started my career as an SQL developer in a small company and has some knowledge in MSBI (Microsoft Business Intelligence) where SSIS, SSAS and SSRS are ETL, data lake and reporting services are part of MSBI. I had this formal learning from a local institute. The major motivation for doing the first job was my school friend. she was the one to guide me to learn Databases. Lucky to have her as my friend.
第一份工作:
我的职业生涯开始于一个小公司的结构化查询语言（SQL：Structured Query Language）开发人员，并有一些MSBI(微软商业智能)的知识，其中SSIS, SSAS和SSRS是提取转换加载，数据湖和报告服务是MSBI的一部分。我是在当地的一个机构正式学习的。我做第一份工作的主要动机来自于我的同学，是她指导我学习数据库，有她这样的朋友我很幸运。
Being ambitious in my life is the best advantage I had which made me think about the way people are working for meagre salaries and the way they are in their comfort zones made me look into what other challenging career paths/technologies are available.
I am talking about 2013, where my managers had 12 years of work experience with 12 lakhs as their salary and they are working in the same company for 12 years in their comfort zone.
Then after thorough research, I found a new thing called Data Science where only 2 institutes were providing the course and the course fee is more than 3 lakhs in 2013.
After connecting previous students of the institute on lixedin and taking the decision along with 2 of my friends we joined INSOFE which is the best decision I have taken.
The course is for 6 months every weekend and to join the institute you have to take their test and only 37 people are chosen for 1 batch and only 2 batches were run in parallel.
I was working night shifts during this course which was very tough and never visited my family for 6 months. It was very tough to work at night and attend the classes during day time.
R is the language that has been taught during the course and once the course is done I started looking into other opportunities.
选择数据科学职业轨迹（地点：海得拉巴）：
面对生活有雄心壮志中是我拥有的最好的优势，这让我思考人们为微薄的薪水而工作的方式，以及他们在舒适区的方式，让我思考还有哪些其他具有挑战性的职业道路/技术可用。
我说的是2013年，我的经理们有12年的工作经验，工资为120万，他们在同一家公司工作了12年，在自己的舒适区工作。
然后经过深入研究，我发现了一个新事物，叫做数据科学，在2013年，只有两个研究所提供了这门课程，课程费用超过了30万。
在lixedin上联系了该学院以前的学生，并与我的两位朋友一起做出决定加入了其中，这是我做出的最好的决定。
该课程每个周末授课，为期6个月，要加入该研究所，你必须参加他们的测试，每批只有37人，同时进行两批次教授。
我上这门课的时候上夜班。这门课很难以至于我有6个月没去看望我的家人。晚上工作，白天上课真的很困难。
R编程语言是课程中教授的语言，课程结束后，我开始寻找其他机会。
After looking for opportunities I have been sexted as a Data Scientist by a startup company in Bangalore.
Not more than 40 people were working in that company but the team was really amazing. From CEO to my manager everyone is from US ivy league universities. My manager has a doctorate in Network Engineering from Purdue University. You can imagine what could be his expectations.
He is the best manager I had till now. He uated where I am good at and where I have to improve. He nurtured me with working ethics and the way to learn. He encouraged me a lot which was the main reason for the confidence I have built up now.
He used to make me explain every topic in Data Science with advanced math to him every day which made my communication skills a big boost and also took part-time opportunities in teaching Data Science.
I have been associated with a number of Data Science institutes and taught for nearly 40 batches till now.
Here I learnt to use Python for Data Science and sidelined R.
转移到班加罗尔：
在寻找机会之后，我被班加罗尔的一家初创公司选为数据科学家。
在那家公司工作的人不超过40人，但团队真的很棒。从CEO到我的经理，每个人都来自美国常春藤盟校。我的经理拥有普渡大学网络工程博士学位，你可以想象他的期望是什么。
他是我迄今为止最好的经理。他评估了我擅长的地方和需要改进的地方。他用工作道德和学习方法培养了我。他给了我很多鼓励，这是我现在建立信心的主要原因。
他曾经让我每天用高等数学向他解释数据科学中的每一个话题，这让我的沟通能力大大提高，还兼职教授数据科学。
到目前为止，我已经与多家数据科学研究所合作，并教授了近40批次。
在这里，我学会了将Python用于数据科学，并边缘化了R编程语言。
I shifted companies and learnt different techniques in Data Science, made amazing friends and became SME in the Retail industry.
I have good knowledge of AWS, Azure and GCP and deployed all ML models in major cloud providers which got an opportunity with one of the top Data Analytics teams where I am working as a Data Science Manager.
目前的工作:
我换了几家公司，在数据科学中学习了不同的技术，结交了很棒的朋友，成为了承接零担业务的中小企业。
我熟悉AWS、Azure和GCP，并在主要的云提供商部署了所有的ML模型，这些提供商获得了一个顶级数据分析团队的机会，我在那里担任数据科学经理。
Many would be interested in Data Science salaries. I never thought in my life that I could get this salary in my life. At a point in time, I was earning a seven-figure salary a month by working for multiple projects as sub contracts.
工资:
很多人会对数据科学的薪水感兴趣。我从来没想过我这辈子能拿到这么高的薪水。有一段时间，我通过为多个项目做分包工作，每月能挣到七位数的薪水。
A Data Analyst is someone who works with huge volumes of raw data and then analyses and predicts future outcomes. They would take the raw data and display it in a meaningful manner that not only makes the information apparent but is also more valuable for decision making.
数据分析师是处理大量原始数据，然后分析和预测未来结果的人。他们会把原始数据以有意义的方式显示出来，这不仅使信息更明显，而且对制定决策更有价值。
Designing and maintaining databases
Researching data from primary and secondary sources and then reorganising data
Interpreting data using statistical tools
Preparing reports for further usage and research purposes
The job prospects in the field of data science are also increasing rapidly. The average salary of a data scientist in India is Rs. 698,412. Hence the career growth in this field is immense.
However, before entering this field it is important to equip yourself with some of these basic skills ;
数据科学家的角色；
设计和维护数据库；
研究主要和次要来源的数据，然后重组数据；
使用统计工具解释数据；
为进一步使用和研究目的准备报告；
数据科学领域的就业前景也在迅速增加。在印度，数据科学家的平均工资是698,412卢比。因此，这个领域的职业发展是巨大的。
然而，在进入这个领域之前，让自己具备这些基本技能是很重要的;
原创翻译：龙腾网 http://www.ltaaa.cn 转载请注明出处
Being well versed with at least one coding language
Having a suitable graduation degree - for example, a degree in the field of computer science will help you in further training
Once you have check-listed the basic skill sets needed to move further in this field, you then need proper domain-specific training from professional institutes like LEARNBAY, UDEMY ETC.
If you are an aspiring data scientist or a working professional who is looking forward to getting some in-depth knowledge in this field, or if you are looking for an opportunity to get your hands on some real-life projects and learn about data science, artificial intelligence, and machine learning, then all you need is proper professional training from a good data science training institute.
Learning can be a daunting task as this field is very vast. Both for freshers and working professionals, training plays a very constructive role. I would recommend you to learn everything about data analytics and domain specialisation via a certification program from institutes like Learnbay .
数学和统计技能；
至少精通一种编码语言；
拥有一个合适的毕业学位，例如，计算机科学领域的学位将帮助你接受进一步的培训；
一旦你拥有了在这个领域进一步发展所需的基本技能，你就需要从LEARNBAY、UDEMY等专业机构获得特定领域的培训。
如果你是一位有抱负的数据科学家或专业人士，希望在这个领域获得一些深入的知识，或者如果你正在寻找一个机会来参与一些实际项目，学习数据科学、人工智能和机器学习，然后你只需要从一个好的数据科学培训机构接受适当的专业培训。
学习可能是一项艰巨的任务，因为这个领域内容非常广返。无论是新生还是在职专业人士，培训都起着非常建设性的作用。我建议你通过Learnbay等机构的认证项目学习有关数据分析和领域专业化的所有知识。
数据科学培训机构在你的数据科学职业生涯中扮演着重要的角色，因为这是一个非常广阔和复杂的领域，需要专业人士的职业帮助。因此，像Learnbay这样的培训机构将帮助你获得机器学习、深度学习和人工智能课程的认证。此外，这个平台将帮助您以非常实用和特定领域的方式学习数据科学，让我们进一步了解它们的特性。
Learnbay treats domain specialisation as one of the most important things, which is beneficial for someone who's going to become a data scientist. As you get the choice to sext from over several domains that suit you the most. Following are the different options available -
Sales, Marketing and HR
Retail Ecommerce and Supply Chain
Banking, Finance, and Insurance
Healthcare Pharma and Clinical Research
Manufacturing and Telecom
Media Hospitality and Transportation
Energy, Oil, and Gas
You can take up different domains such as Human Resources and Marketing and Telecommunications and Manufacturing and many more.. So it would be a very informative yet streamlined learning process for you.
不同领域专业化学习：
Learnbay将各个领域专业化视为最重要的事情之一，这对即将成为数据科学家的人来说是有益的。你可以从多个最适合你的领域中进行选择。以下是可用的不同选项：
销售、市场营销和人力资源
零售电子商务和供应链
银行、金融和保险
医疗制药与临床研究
制造业和电信业
媒体接待和运输
能源、石油和天然气
你可以从事不同的领域，如人力资源、市场营销、电信和制造等。因此，这将是一个非常有益的学习过程，但也简化了学习。
As this course by Learnbay is specially designed for working professionals, after completion of this course, if you don't get a job, it guarantees you placements or a 100% money-back guarantee.
Live Classes and flexible subscxtion plans :
If you are one of those working professionals who has decided to transition his/her career towards data science, Learnbay is the best platform you can find as this course is best suitable for working professionals. Live flexible classes are organised for those who want proper guidance and knowledge for transition into data science. You will be focusing on skills that make you ready to deal with the industry.
Free counselling with professionals:
Being new in the field of data science, we have a lot of queries in our minds. To solve this problem, Learnbay provides a free counselling service with experts who can guide you.
So for a working professional Learnbay is giving so many exclusive features that too at a very affordable price . For an aspiring data scientist who seeks to learn more practically through domain specialisation , Learnbay is the best data science training institute .
Hope I answered your question !
100%就业或退款保证：
由于Learnbay的这门课程是专为在职专业人士设计的，因此在完成这门课程后，如果你没有找到工作，它会保证你获得就业机会或100%的退款保证。
实时课程和灵活的订阅计划：
如果你是决定将职业生涯转向数据科学的在职专业人士之一，Learnbay是你能找到的最好的平台，因为本课程最适合在职专业人士。为那些希望获得适当指导和知识以过渡到数据科学的人组织了实时灵活的课程。你将专注于使你准备好应对这个行业的技能。
免费咨询专业人士：
作为数据科学领域的新手，我们脑子里有很多疑问。为了解决这个问题，Learnbay提供免费咨询服务，专家可以为你提供指导。
因此，对于一个工作的专业人士来说，Learnbay提供了如此多的独家功能，而且价格非常合理。对于一位有抱负的数据科学家来说，Learnbay是最好的数据科学培训机构，他希望通过领域专业化学习更多实际知识。
希望我回答了你的问题！
高拉夫·查特吉，计算机科学与机器学习，卡纳塔克中央大学(2019)
Also I will make sure to include the tricks in my answer that worked for me.
So Let's begin, Shall we?
I will be answering this question, keeping in mind that a bunch of readers could be complete newbies into programming.
So addressing non-computer science students. Firstly, you need to work a lot on your problem-solving skills which is going to help you code effortlessly. You can achieve this by learning Data structures & Algorithms and coding in it. Also, DS & Algo are the building block of computer science so it will definitely help you on your Journey towards excellence in coding.
After you are comfortable with problem-solving, you should stick to the below mentioned points:
Opt for a good course on Machine learning and study it thoroughly to become well versed with all it’s concepts.
Practice machine learning problems on Kaggle: Your Machine Learning and Data Science Community which will help you gain confidence and give you enough hands-on skills.
Post your projects on GitHub, lixedIn and also you can use youtube to showcase your skills
Now it’s Time to market yourself. Make a clean and creative online portfolio and a strong resume based on ML. Start applying to your desired companies and surely circumstances will bend in your favour and soon you will become something you have worked so hard for and that is “Data scientist”
我本人是一名数据科学家，因此我有资格回答你的问题。
此外，我会确保在我的答案中加入对我有用的技巧。
让我们开始吧，好吗？
我将回答这个问题，记住一大群读者可能是编程的新手。
所以，向非计算机科学专业的学生说的：
首先，你需要在解决问题的能力上下功夫，这将帮助你毫不费力地编写代码。你可以通过学习数据结构、算法和编码来实现这一点。
此外，数据集和算法是计算机科学的基石，因此它肯定会帮助你在编码方面走向卓越。
在你对解决问题感到满意之后，你应该坚持以下几点：
选择一门关于机器学习的好课程，并对其进行彻底的学习，以熟悉其所有概念。
在Kaggle（一个数据建模和数据分析竞赛平台）上练习机器学习问题：你的机器学习和数据科学社区将帮助你获得自信，并提供足够的实操技能。
在GitHub、lixedIn上发布你的项目，也可以使用油管展示你的技能。
现在是推销自己的时候了。在机器语言的基础上制作一份干净、有创意的在线投资组合和一份强有力的简历。开始在你想要的公司申请工作机会，环境肯定会对你有利，很快你就会成为你一直努力追求的身份，那就是“数据科学家”